DESIGN OF AN INTELLIGENT ROOM TEMPERATURE AND HUMIDITY CONTROL SYSTEM AND COMPARATIVE ANALYSIS OF TRIMF AND TRAPMF MEMBERSHIP FUNCTIONS BASED ON SIMULINK MODEL
DOI:
https://doi.org/10.5281/zenodo.20232531Keywords:
In fuzzy logic control, however, the control signal changes gradually through membership functions and the rule base, positively affecting system stability.Abstract
The operation process of the temperature control system in the MATLAB environment using the Fuzzy Logic Toolbox is analyzed through two main visual analysis tools — Surface Viewer and Rule Viewer. These tools enable the visual analysis of nonlinear relationships between the input and output variables of the fuzzy control system, rule activation processes, and the formation of the control signal.
The behavioral characteristics of the system were observed and evaluated through these tools. Such an approach is important for understanding the internal mechanisms of the fuzzy inference process, determining the efficiency of the rule base, and evaluating the overall stability of the system. The Surface Viewer and Rule Viewer modules of MATLAB Fuzzy Logic Toolbox graphically and dynamically demonstrate the operation of the fuzzy system.
The Surface Viewer is an important visualization tool within MATLAB Fuzzy Logic Toolbox that displays the dependence of the fuzzy controller output signal on two input parameters in the form of a three-dimensional surface graph. Through this graph, the interaction between the fuzzy rule base and membership functions, as well as the overall control characteristics of the system, can be evaluated. In scientific studies, such graphs are widely used to determine system stability, sensitivity, and smoothness of control.
In the designed system, the Surface Viewer graph illustrates the dependence of the Heat-Fan-Speed output parameter on the Current-Temperature and Deviation from Set Temperature input parameters. The coordinate axes of the graph are defined as follows (Figure 3.3.1):
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